This presentation explores how advanced sensitivity analysis methods within an atmospheric chemical transport model (CTM) can be used to inform air quality management decisions. We do so by developing and applying reverse sensitivity (or adjoint) method in a state-of-the-art CTM to various applications. These applications demonstrate how an adjoint model provides unparalleled granularity across locations and emission sectors. As a prime example, the method is applied to examine the impact of decarbonization policies on air quality by estimating co-benefits of reducing CO2 emissions from a range of combustion sources.  Location-specific sectoral co-benefits will be presented at local, national, and hemispheric resolutions. The adjoint-derived results are novel in two important ways. First, they provide location-specific health co-benefit estimates for various sectors and at different resolutions. Second, we show how the method can be extended to estimate location-specific environmental justice co-benefits at urban scale. Population health and environmental justice co-benefits can also be calculated as monetized estimates (i.e., $/ton-CO2), allowing for direct comparison with the social cost of carbon as a combined measure of societal impact. Health co-benefit estimates for the year 2016, and for the northern hemisphere (108 km), the United States (12 km), and the city of Los Angeles (1 km) will be presented as examples. Environmental justice co-benefits are calculated for Los Angeles and for exposure disparities with respect to race and income. The results demonstrate how location-specific co-benefits may be used to conduct a more holistic, and yet granular accounting of benefits of decarbonization. Furthermore, we discuss how the inclusion of population health and environmental justice in the accounting of mitigation benefits has the potential to expand the narrative and broaden the reach of climate discourse among decision makers and the public alike.